Generative AI offers the opportunity to transform the manufacturing and automotive industries. In this session, we will share Google Cloud's perspective and specific use cases that can boost productivity and operational efficiency. The session will also feature customer success stories and a discussion with organizations at the forefront of generative AI use.

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Get a behind-the-scenes look at Walmart's data and AI platform. We'll dissect their use of BigQuery, Spark, and large language models to run complex multi-modal data pipelines. We will deep dive into the choices with various engines (SQL, pySPARK) and technologies along with the corresponding tradeoffs. Gain exclusive insights to implement into your own projects.

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In this session, Gemini leads will cover the tips, tricks, insights and lessons learned from helping over 30-plus teams at Google Cloud build world-class developer productivity tools using generative AI. Session highlights include: the "secret sauce" behind GenAI Chat for both IDE and Cloud Console experiences; hidden “gotchas” behind code completion and generation experiences for over 21 languages; how developer teams have to change their processes when adding nondeterministic technology to their stack, and much more.

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Unleash the power of artificial intelligence (AI) to maximize embeddings to solve your unique business challenges. Join experts from Google Cloud and Two Sigma for an exploration of Vertex AI's text and multimodal embedding capabilities. These models drive innovation across different industries and use cases.

Two Sigma and Google Cloud draw on previous work to review their derivation of a framework for objectively evaluating embedding models, then the application of this framework against a textual similarity task using the Massive Text Embedding Benchmark (MTEB).

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David Austin is a data scientist and a member of one of the top teams in Kaggle’s competition to detect AI-generated text. He’ll be sharing his first-hand learnings and insights on this rapidly growing problem space.

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Join this demo-driven session to transform your development workflow with Gemini, your AI-powered collaborator. We'll start with a blank canvas and build, test, and deploy an application, leveraging Gemini's assistance at every stage. Explore how Gemini not only enhances your coding efficiency but also helps you understand and improve existing codebases. By the end, you'll discover a range of ways Gemini can supercharge your application development journey.

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BigQuery allows you to generate multimodal embeddings and perform vector searches directly on your data without complex preprocessing steps. Simplify the process of finding relevant data, identifying patterns and trends, and clustering similar objects together.

Learn how to generate embeddings using familiar BigQuery SQL syntax with multimodal inputs (text, images, audio). We’ll then review how to use BigQuery’s vector search capabilities to explore data in new and innovative ways, leading to faster decision-making and improved insights.

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Ready to level up your infrastructure, Google Kubernetes Engine, and networking skills with the power of Gemini? Join this session to learn how large language models work and how it applies to roles in infrastructure, DevOps, and networking.

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Learn how to talk to your data, and unlock insights with greater ease with Gen AI-powered Search and Conversation. See how Workday is putting natural language to work using Vertex AI to make it more accessible to extract insights for technical and non-technical users. Please note: seating is limited and on a first-come, first served basis; standing areas are available

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Join experts from Box, Typeface, Glean, CitiBank, and Securiti AI for actionable tips to effectively implement AI-powered apps across your enterprise. We'll discuss real use cases, implementation best practices, and how to measure returns on investment — whether that's in marketing, financial services, HR, or beyond.

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Discover how approachable and versatile building custom generative AI solutions for Google Workspace can be with Google Apps Script. In this session, we‘ll explore how developers are creating innovative integrations between Gemini‘s powerful large language models and Google Workspace. Get real-world examples of how AI can enhance Google Workspace functionality, and learn about the potential of custom solutions to address unique needs. Get ready to be inspired – the evolution of leveraging AI within Google Workspace is just beginning.

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Web3 is garnering ever more attention by having a disruptive impact on games around the world. This past year, we’ve seen web3 ecosystems like Sequence, Polygon, Solana, and Aptos build and incubate their own game studios, while others have been partnering with game studios - from indie to AAA - to integrate web3 primitives into games and set the stage for a new generation of titles to delight players. This panel will explore what’s new, and what’s not so new about games as they relate to web3, and how companies leveraging this technology attract new players, create novel experiences, and unlock rewarding monetization models.

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This session explores how agencies are using Google Cloud to unlock critical data insights. These insights streamline operations and improve mission outcomes. You'll learn how these agencies are planning the responsible adoption of AI to further accelerate these gains. Discover how Google Cloud empowers agencies to better serve their communities, respond with faster services, and ultimately fulfill their missions with ever-increasing impact.

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Default service accounts provide the flexibility to get started, but often have excess permissions when used in production. How do we find a balance between ease of use for developers and the security demands in production environments? This session covers the common pitfalls that can occur with default service accounts, how to move beyond default service accounts and use custom IAM roles to follow the principle of least privilege, and how to automate alerts to balance the needs of developers and security teams.

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The emergence of foundation models and generative AI has introduced a new era for building AI systems. Selecting the right model from a range of architectures and sizes, curating data, engineering optimal prompts, tuning models for specific tasks, grounding model outputs in real-world data, optimizing hardware – these are just a few of the novel challenges that large models introduce. Delve into the fundamental tenets of MLOps, the necessary adaptations required for generative AI, and capabilities within Vertex AI to support this new workflow.

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Accessing mission-critical data in a nonintrusive fashion will be critical for enabling operational analytics, and with the evolution of generative AI, enterprises are building RAG-based gen AI applications that require access to operational data. Datastream is a simple, serverless data-streaming platform that organizes the ingesting, processing, and analyzing operational data to support AI/ML and RAG apps. Experts from RocketMoney and Intuit Mailchimp will share how they’re using Datastream to solve for Operational Analytics and beyond.

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Discover how Mercado Libre and Grupo Boticario utilize gen AI to transform their respective industries, enhancing product and content discovery. Please note: seating is limited and on a first-come, first served basis; standing areas are available

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As the sprawling web of applications continues to expand, platform engineers today are grappling with ever-increasing security, reliability, and productivity challenges. Join our experts in this session to learn how AI-assisted automation can help platform engineers standardize API creation, automate spec generation and reviews, ensure comprehensive visibility across all enterprise APIs, enforce consistent security standards, and unlock new revenue streams.

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As generative AI applications mature, retrieval-augmented generation (RAG) has become popular for improving large language model-based apps. We expect teams to move beyond basic RAG to autonomous agents and generative loops. We'll set up a Weaviate vector database on Google Kubernetes Engine (GKE) and Gemini to showcase generative feedback loops.

After this session, a Google Cloud GKE user should be able to: - Deploy Weaviate open source on GKE - Set up a pipeline to ingest data from the Cloud Storage bucket - Query, RAG, and enhance the responses

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Developing GenAI applications quickly can represent a daunting challenge for today's businesses. But no longer. In this session, we'll demonstrate how Deloitte's AI Studio enables rapid development of compelling GenAI applications in no-code, low-code and pro-code environments, while working seamlessly with Google Cloud native tools. We'll explore the platform's suite of pre-configured capabilities and accelerators, and highlight use cases. Please note: seating is limited and on a first-come, first served basis; standing areas are available. By attending this session, your contact information may be shared with the sponsor for relevant follow up for this event only.

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